SURVEY ON IMPROVED ARTIFICIAL BEE COLONY ALGORITHM FOR BALANCING EXPLORATION AND EXPLOITATION

@inproceedings{Thilak2017SURVEYOI,
  title={SURVEY ON IMPROVED ARTIFICIAL BEE COLONY ALGORITHM FOR BALANCING EXPLORATION AND EXPLOITATION},
  author={K. Deepa Thilak},
  year={2017}
}
Today many fields like engineering, management, and economy faces many optimization problems which are needed to be solved by meta-heuristics techniques. The Artificial Bee Colony (ABC) algorithm is a population-based stochastic swarm intelligence algorithm finds applications in most of the fields. The problem with ABC is its slow convergence speed due to the poor exploitation capability and falls into local minima in the case of multimodal functions. The efficiency of the standard ABC lies in… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 37 REFERENCES

Efficiency analysis of swarm intelligence and randomization techniques

  • X. S. Yan
  • Journal of Computational and Theoretical…
  • 2012
Highly Influential
6 Excerpts

K

  • S. Z. Zhang, C.K.M. Lee, H. K. Chan
  • L. Choy and Z. Wu.: Swarm intelligence applied in…
  • 2015
Highly Influential
5 Excerpts

A

  • M. Kumar
  • Sharma and R. Kumar.:Optimization of test cases…
  • 2011
Highly Influential
5 Excerpts

“ A microartificial bee colony based multicast routing in vehicular ad hoc networks

  • Oussama Ait Sahed
  • Ad Hoc Networks
  • 2016

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